glmmPQL                 package:MASS                 R Documentation

_F_i_t _G_e_n_e_r_a_l_i_z_e_d _L_i_n_e_a_r _M_i_x_e_d _M_o_d_e_l_s _v_i_a _P_Q_L

_D_e_s_c_r_i_p_t_i_o_n:

     Fit a GLMM model with multivariate normal random effects, using
     Penalized Quasi-Likelihood.

_U_s_a_g_e:

     glmmPQL(fixed, random, family, data, correlation, weights,
             control, niter = 10, verbose = TRUE, ...)

_A_r_g_u_m_e_n_t_s:

   fixed: a two-sided linear formula giving fixed-effects part of the
          model. 

  random: A formula or list of formulae describing the random effects. 

  family: a GLM family. 

    data: an optional data frame used as the first place to find
          variables in the formulae. 

correlation: an optional correlation structure. 

 weights: optional case weights as in 'glm'. 

 control: an optional argument to be passed to 'lme'. 

   niter: maximum number of iterations. 

 verbose: logical: print out record of iterations? 

     ...: Further arguments for 'lme'. 

_D_e_t_a_i_l_s:

     'glmmPQL' works by repeated calls to 'lme', so package 'nlme' will
     be loaded at first use if necessary.

_V_a_l_u_e:

     A object of class '"lme"': see 'lmeObject'.

_R_e_f_e_r_e_n_c_e_s:

     Schall, R. (1991) Estimation in generalized linear models with
     random effects. _Biometrika_ *78*, 719-727.

     Breslow, N. E. and Clayton, D. G. (1993) Approximate inference in
     generalized linear mixed models. _Journal of the American
     Statistical Association_ *88*, 9-25.

     Wolfinger, R. and O'Connell, M. (1993) Generalized linear mixed
     models: a pseudo-likelihood approach. _Journal of Statistical
     Computation and Simulation_ *48*, 233-243.

     Venables, W. N. and Ripley, B. D. (2002) _Modern Applied
     Statistics with S._ Fourth edition.  Springer.

_S_e_e _A_l_s_o:

     'lme'

_E_x_a_m_p_l_e_s:

     library(nlme)
     summary(glmmPQL(y ~ trt + I(week > 2), random = ~ 1 | ID,
                     family = binomial, data = bacteria))

